Institute for Data Ecosystem Advancement

Building the
infrastructure
public data
deserves.

IDEA advances the science and practice of integrated data systems — developing standards, conducting research, and equipping communities to share data lawfully, purposefully, and well.

3
Institutional layers
studied
9
Separate projects spanning
3 geographic ecosystems
87
Days to first data product
under federated design
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What We Do

The field needs research,
standards, and practice.

Most communities building integrated data systems face the same structural problems — and solve them alone. IDEA exists to change that.

01

Research & Measurement

We develop diagnostic frameworks for measuring governance burden, data product value, and structural readiness across integrated data systems — grounded in operational evidence from real communities.

02

Field Standards

We produce practitioner standards for IDS design, governance architecture, and inter-IDS information exchange — developed cross-site and published openly for use across the national network.

03

Capacity & Education

We build practitioner capacity through workshops, training, and community education — including pathways for underrepresented communities into data and technology careers in the public interest.

Current Work

Active research
and field initiatives.

IDEA's current portfolio spans governance diagnostics, privacy-enhancing technologies, and the first cross-site interoperability standards for integrated data ecosystems.

Standards
Inter-IDS Interoperability Framework
A cross-site standards alignment across three institutional layers — local, county, and state — producing a replicable readiness package for any IDS assessing capacity for inter-IDS information exchange. Developed in partnership with AISP across Tulsa and Connecticut.
In Development
Research
Governance Saturation in Integrated Data Systems
An exploratory diagnostic study identifying how governance burden can be measured from routine operational artifacts — before it manifests as project failure. Applies a two-dimensional model of governance adequacy distinguishing structural resolution from functional capacity.
Published
Co-Publication
Privacy-Enhancing Technologies in Public Data Ecosystems
A practitioner report on Connecticut's statewide PET implementation, co-published with Georgetown University's Massive Data Institute. Includes recommendations for cross-IDS governance standards as the necessary next step for the field.
Forthcoming
Theory
Structured Incompleteness Theory
A theoretical framework explaining why coordination across institutions is structurally constrained — and why mismatch is a design problem rather than a failure of will or competence. Underpins IDEA's applied diagnostic work and governance standards development.
Working Paper

The Diagnostic Argument

Why data partnerships stall.

"Persistent governance delay may signal structural mismatch — not insufficient capacity alone."

Across nine IDS projects and thirty governance episodes, stalled authorizations occur only in custodial architecture — at coupling loads below those handled under federated design. The difference between a project that delivers in 87 days and one that takes 624 is not trust, leadership, or staffing. It is the structural resolution of the governance boundary.

IDEA's research makes this diagnosable from artifacts every organization already produces — before failure, not after.

Structural Resolution
The range of request types a governance boundary can distinguish and route appropriately.
Discrete and combinatorial. Altered through governance design, boundary decomposition, domain-specific review, or architectural choices. No amount of staffing compensates for a boundary that conflates structurally distinct request types.
Functional Capacity
The rate at which a governance boundary processes and authorizes requests it already recognizes.
Continuous and temporal. Improved through staffing, expertise, templates, and facilitation. Necessary but insufficient when structural resolution is the binding constraint.
The Coarsening Cascade
What happens when capacity pressure leads to conflation.
Capacity pressure leads to coarsening of request types, which leads to conflation, which produces misrouted governance — friction attributed to relationships when the underlying problem is structural. IDEA's diagnostic framework identifies this pattern early.

Partners & Collaborators

IDEA's work is grounded in active partnerships across the practitioner, academic, and government communities working to advance integrated data systems in the public interest.

AISP at Penn
Co-publisher · Network
Georgetown MDI
Academic Co-author
State of Connecticut
Research Site
Tulsa IDS Ecosystem
Research Site · Home
Asemio
Tech Innovation Partner

About IDEA

IDEA is a research and field-building fund housed at the Tulsa Community Foundation, established to advance the science and practice of data-driven community improvement.

Our work spans applied research, practitioner standards development, and community education — with particular focus on the governance and technical infrastructure that allows agencies, nonprofits, and governments to share data in ways that are lawful, purposeful, and equitable. We publish openly and develop standards collaboratively.

Established
Tulsa Community Foundation
Focus Areas
Governance Architecture · Privacy-Enhancing Technologies · IDS Standards · Applied Research
Network
AISP Advisory Board · Georgetown MDI · National IDS Practitioner Community
Forthcoming
AISP Annual Convening · Georgetown MDI Summer Institute on PETs

Work with us.
Build with the field.

IDEA welcomes collaboration with researchers, practitioners, foundations, and government partners working to advance integrated data systems in the public interest.

Get in Touch View Our Research